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sod-ship
Start-of-day git sync — commit, push, pull all 5 projects, update submodules, then claude-sync.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
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Start-of-day git sync — commit, push, pull all 5 projects, update submodules, then claude-sync.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
Meta-orchestrator that decomposes user goals into agent execution plans with model routing and dependency ordering, optionally pursuing them via Goal Mode with pursuing/paused/achieved/unmet/budget-limited lifecycle states. Maintains a persistent TODO backlog under state/todos/. Pipeline Mode auto-triggers for registered pipelines (report, persona, deep-research, research-report) and executes immediately. Use when: "jarvis", "자비스", "plan how to do X", "decompose this goal", "goal mode", "목표 모드", "pursue this until done", "jarvis goal", "jarvis plan", "자비스 계획", "자비스 목표", "long-running objective", "multi-turn goal", "멀티턴 목표", "장기 목표", "계획 세워줘", "jarvis todo", "자비스 TODO", "보고서 작성해줘", "리포트 만들어줘", "보고서 생성", "분석 보고서", "슬랙에 리포트 보고", "슬랙에 보고서 공유", "리서치해서 슬랙에 보고", "페르소나 분석", "관점 분석해줘", "관점 분석", "딥 리서치", "리서치해서 보고서로". Do NOT use for a single known skill (invoke directly), simple edits, or one-shot tasks. Do NOT use for daily pipeline (use today). Do NOT use for "딥 리서치" without "보고서" → use deep-research-pipeline.
End-to-end playbook to fine-tune and evaluate an LLM on ThakiCloud Metis (kubeflow-llm-training + vLLM serving on compute-h200). Covers served-model data generation, dataset→S3, TrainJob submission (with every admission gotcha), LoRA adapter serving for inference, and gate-based A/B eval. Use when "모델 학습시켜줘", "파인튜닝 돌려줘", "TrainJob 띄워줘", "학습 전후 평가/A/B", "데모 GPU로 학습", "fine-tune on the cluster", "train and evaluate", "serve the adapter and compare". General across models. Do NOT use for local/Colab training (use colab-unsloth-finetune) or serving-only ops (use demo-llm-inference-test).
Sync the #ai-platform-internal-qa Slack channel (demo.thakicloud.net QA reports) to a local corpus with full threads, filter out completion-tagged (완료/확인_완료) items, and dedup-check a new QA finding before posting it in the team's expert template. Use when "QA 이슈 올리기 전 중복 체크", "내부 QA 슬랙 싱크", "demo qa 중복 확인", "이 버그 이미 올라왔나", "internal-qa 채널", "check if this QA issue is a duplicate", "post QA finding". Do NOT use for GitHub issue dedup (use github-issue-dedupe), monitor/alert spam throttling (use slack-alert-dedup-cooldown), or general Slack posting (use scripts/slack_post_message.py).
Generate THAKI Design System (@thaki/tds) desktop-console UI from text / sketch / screenshot via a two-stage IR (UX-IR -> TDS-IR) with a deterministic compiler + validation gate + repair loop. Use when "TDS로 UI 생성", "화면 생성기", "디자인시스템 컴포넌트 트리 생성", "UI generator", "screenshot to TDS". Owns the TDS Component Registry (61 primitives) and the synthetic data engine for training a UI-gen model. Do NOT use for freehand React coding (use frontend-design) or Figma sync (use figma-to-tds).
Turn a known cartoon/comic character into a KakaoTalk-quality emoticon set (360x360 transparent, animated). Extracts a clean single-character reference, then generates held-cel sprite sheets with gpt-image-2 (body held, one part moves), splits/keys/stabilizes them, and compiles to KakaoTalk spec + GIF + PNG. Use when "이모티콘 만들어줘", "카카오 이모티콘", "캐릭터 이모티콘화", "움직이는 이모티콘", "emoticon set", "kakaotalk sticker set", "animate my character", "sprite emoticon". Do NOT use for one-off single stickers/messengers other than Kakao (use sticker-forge `stickerforge make`), plain image generation (use gpt-image-2), a pose sheet meant for dance/video (use pose-sheet-to-animation), or video (use video-producer).
Resume/continue development of 눈치맵 (nunchi-map) — a real-time local crowd/wait/on-site-photo app (대국민 눈치게임): enter a destination, see how crowded it is now, expected wait, and live '지금 뜨는 곳' ranking. Routes to the repos, explains architecture + how to run/verify, and lists the exact next gaps. Use when the user says "눈치맵", "누치맵", "nunchi-map", "대국민 눈치게임", "혼잡도 앱", "지금 뜨는 곳", or asks to continue/extend/deploy that app or its landing page. Do NOT use for ThakiCloud product repos (see [[thaki-platform-repos]]) or generic Go/React scaffolding unrelated to this app.
SOC 職業分類に基づく
| name | sod-ship |
| description | Start-of-day git sync — commit, push, pull all 5 projects, update submodules, then claude-sync. |
| disable-model-invocation | true |
Synchronize all managed repositories at the start of the day.
praxis (tracks main) and thaki-ui (tracks develop) are pulled to the LATEST upstream commit and their gitlink bumps committed; the others stay pinned to their recorded SHA:# this repo only — pull praxis(main) + thaki-ui(develop) to latest, commit each gitlink if it moved
for sm in praxis thaki-ui; do
git -C ~/thaki/ai-platform-strategy submodule update --init --remote "$sm" 2>&1 | tail -3
if ! git -C ~/thaki/ai-platform-strategy diff --quiet -- "$sm"; then
git -C ~/thaki/ai-platform-strategy add "$sm"
git -C ~/thaki/ai-platform-strategy commit -m "chore: bump $sm submodule to latest" 2>&1 | tail -2
fi
done
# other submodules: checkout recorded SHA (no --remote) to avoid surprise bumps
git -C ~/thaki/ai-platform-strategy submodule update --init ai-suite ai-platform-webui thaki-cloud-assistant 2>&1 | tail -3
/cursor-sync 수동 실행).venv). This is what makes a freshly-pulled repo actually work on the second machine.# this repo only; auto-heal (user-approved): clone missing source repos, recreate
# broken symlinks, rebuild .venv only if missing/version-mismatched (idempotent — healthy = skip)
bash scripts/env_bootstrap.sh --heal 2>&1 | tail -20
Report the heal summary in the SOD output. A warn (e.g. webwright with no
source_repo, or a missing global CLI) does NOT fail SOD — surface it as an
action item. venv rebuild is skipped when already healthy, so this is cheap on
the day-to-day machine and only does real work right after a fresh clone.
Verified 2026-06-11: all repos track main (not dev); research is its own dir;
macro-factor-dashboards may be absent locally; ai-model-event-stock-analytics
is on the hyojunguy account (push may need that auth — skip gracefully).
| Repo | Branch | Path | Origin |
|---|---|---|---|
| ai-platform-strategy | main | ~/thaki/ai-platform-strategy | sylvanus4/ai-strategy |
| realtime-translator | main | ~/thaki/realtime-translator | sylvanus4/realtime-translator |
| github-to-notion-sync | main | ~/thaki/github-to-notion-sync | sylvanus4/github-to-notion-sync |
| ai-template | main | ~/thaki/ai-template | sylvanus4/cursor-template (renamed) |
| research | main | ~/thaki/research | sylvanus4/research |
| ai-model-event-stock-analytics | main | ~/thaki/ai-model-event-stock-analytics | hyojunguy/… (diff account) |
| macro-factor-dashboards | main | ~/thaki/macro-factor-dashboards | sylvanus4/… (may be absent) |
Do NOT hardcode the branch — read each repo's actual upstream
(git -C <dir> rev-parse --abbrev-ref --symbolic-full-name @{u}) before push/pull.
Run commit-preflight-guard and fleet-divergence-doctor before mutating any repo.
dev/mainoutputs/, state/ are runtime data (cron-managed) — do not force-commit in a loop#효정-할일 at the end (eod-ship Phase 6 parity); best-effort via slack_post_message.py, never blocks completion